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Using support vector machine to development early warning system for financial crisis.
| Content Provider | CiteSeerX |
|---|---|
| Abstract | This paper proposes to utilize support vector machine (SVM) to develop an early warning system for financial crisis. The system focuses on selecting proper financial market variables and finding data mining classifier which produces signal for possible crisis when training data is sparse. For this purpose, economic financial condition indicator (Econ-FCI) monitoring financial market is built on SVM and its result is compared to Econ-FCI on other data mining classifiers such as multinomial logistic regression (MLR), decision tree (DT), case-based reasoning (CBR) and neural networks (NN). This study empirically performed for Korean financial market. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Financial Crisis Support Vector Machine Development Early Warning System Early Warning System Case-based Reasoning Training Data Data Mining Classifier Decision Tree Multinomial Logistic Regression Economic Financial Condition Indicator Korean Financial Market Possible Crisis Financial Market Neural Network Proper Financial Market Variable |
| Content Type | Text |
| Resource Type | Article |
